Count data are primarily categorised as cross-sectional, time series, and panel. Over the past decade, Poisson and Negative Binomial (NB) models have been used widely to analyse cross-sectional and time series count data, and random effect and fixed effect Poisson and NB models have been used to analyse panel count data. However, recent literature suggests that although the underlying distribut...

The study of time series models for count data has become a topic of special interest during the last years. However, while research on univariate time series for counts now flourish, the literature on multivariate time series models for count data is notably more limited. In the present paper, a bivariate integer-valued autoregressive process of order 1 (BINAR(1)) is introduced. Emphasis is pl...

The random coefficient integer-valued autoregressive process was introduced by Zheng, Basawa, and Datta in [55]. In this paper we study the asymptotic behavior of this model (in particular, weak limits of extreme values and the growth rate of partial sums) in the case where the additive term in the underlying random linear recursion belongs to the domain of attraction of a stable law. MSC2000: ...

The purpose of this paper is to introduce and develop a family of Z+-valued autoregressive processes of order p (INAR(p)) by using the generalized multiplication F of van Harn and Steutel (1982). We obtain various distributional and regression properties for these models. A number of stationary INAR(p) processes with specific marginals are presented and are shown to generalize several existing ...

In this paper the integer-valued autoregressive model of order one, con1 taminated with additive outliers is studied in some detail. Moreover, parameter estima2 tion is also addressed. Supposing that the timepoints of the outliers are known but their 3 sizes are unknown, we prove that the conditional least squares (CLS) estimators of the 4 offspring and innovation means are strongly consistent....